Culture-based methods for fecal indicator microorganisms are the standard protocol to assess potential health risk from drinking water systems. However, these traditional fecal indicators are inappropriate surrogates for disinfection-resistant fecal pathogens and the indigenous pathogens that grow in drinking water systems. There is now a range of molecular-based methods, such as quantitative PCR, which allow detection of a variety of pathogens and alternative indicators. Hence, in addition to targeting total Escherichia coli (i.e., dead and alive) for the detection of fecal pollution, various amoebae may be suitable to indicate the potential presence of pathogenic amoeba-resisting microorganisms, such as Legionellae. Therefore, monitoring amoeba levels by quantitative PCR could be a useful tool for directly and indirectly evaluating health risk and could also be a complementary approach to current microbial quality control strategies for drinking water systems.

An inappropriate cross-connection between sewage- and drinking-water pipelines contaminated tap water in a Finnish town, resulting in an extensive waterborne gastroenteritis outbreak in this developed country. According to a database and a line-list, altogether 1222 subjects sought medical care as a result of this exposure. Seven pathogens were found in patient samples of those who sought treatment. To establish the true disease burden from this exposure, we undertook a population-based questionnaire investigation with a control population, infrequently used to study waterborne outbreaks. The study covered three areas, contaminated and uncontaminated parts of the town and a control town. An estimated 8453 residents fell ill during the outbreak, the excess number of illnesses being 6501. Attack rates were 53% [95% confidence interval (CI) 49.5-56.4] in the contaminated area, 15.6% (95% CI 13.1-18.5) in the uncontaminated area and 6.5% (95% CI 4.8-8.8) in the control population. Using a control population allowed us to differentiate baseline morbidity from the observed morbidity caused by the water contamination, thus enabling a more accurate estimate of the disease burden of this outbreak.

We describe a simple and standardised screening system (AREB) for surveillance of antibiotic resistant bacteria in the environment. The system consists of 96 well microplates containing eight sets of breakpoint amounts of 10 different antibiotics. The incubated microplates are read by a desktop scanner and the plate images are analysed by special software that automatically presents the resistance data. The AREB method is combined with a rapid typing method, the PhenePlate system, which yields information on the diversity of the bacteria in the studied samples, and on the possible prevalence of resistant clones. In order to demonstrate the usage of AREB, a comparative study on the resistance situation among 970 Escherichia coli isolates from sewage and recipient water in Sweden, Norway and Chile, was performed. Resistance rates to all antibiotics were markedly higher in hospital sewage than in other samples. Our data indicate that the AREB system is useful for comparing resistance rates among E. coli and other environmental indicator bacteria in different countries/regions. Simple handling and automatic data evaluation, combined with low cost, facilitate large studies involving several thousands of isolates.

Approximately 20% of the 600 First Nations reserves across Canada are under a drinking water advisory, often due to unacceptable levels of bacteria. In this study, we detected fecal bacteria at an alarmingly high frequency in drinking water sources in a fly-in First Nations community, most notably in buckets/drums of homes without running water where Escherichia coli levels ranged from 20 to 62,000CFU/100mL. The water leaving the water treatment plant was free of E. coli and its free residual chlorine concentration (0.67mg/L) was within the range typically observed for treated water in Canada. Water samples from taps in homes served by cisterns, and those sampled from the water truck and community standpipe, always showed unacceptable levels of E. coli (1 to 2100CFU/100mL) and free residual chlorine concentrations below the 0.2mg/L required to prevent bacterial regrowth. Samples from taps in homes served by piped water had lower levels of E. coli (0 to 2CFU/100mL). DNA- and RNA-based 16S rRNA Illumina sequencing demonstrated that piped and cisterns water distribution systems showed an abundance of viable cells of Alphaproteobacteria indicative of biofilm formation in pipes and cisterns. The alpha diversity, based on observed OTUs and three other indices, was lowest in water truck samples that supplied water to the cistern and the low free residual chlorine concentration (0.07mg/L) and predominance of Betaproteobacteria (63% of viable cells) that were immediately detected after the truck had filled up at the water treatment plant was indicative of contamination by particulate matter. Given these findings, First Nation residents living without running water and relying on inadequate water distribution systems are at higher risk of contracting water-born illnesses. We urge all governments in Canada to expand their investments in supporting and sustaining water as a human right in Canada's First Nations communities.

Next-generation sequencing of the V1-V2 and V3 variable regions of the 16S rRNA gene generated a total of 674,116 reads that described six distinct bacterial biofilm communities from both water meters and pipes. A high degree of reproducibility was demonstrated for the experimental and analytical work-flow by analyzing the communities present in parallel water meters, the rare occurrence of biological replicates within a working drinking water distribution system. The communities observed in water meters from households that did not complain about their drinking water were defined by sequences representing Proteobacteria (82-87%), with 22-40% of all sequences being classified as Sphingomonadaceae. However, a water meter biofilm community from a household with consumer reports of red water and flowing water containing elevated levels of iron and manganese had fewer sequences representing Proteobacteria (44%); only 0.6% of all sequences were classified as Sphingomonadaceae; and, in contrast to the other water meter communities, markedly more sequences represented Nitrospira and Pedomicrobium. The biofilm communities in pipes were distinct from those in water meters, and contained sequences that were identified as Mycobacterium, Nocardia, Desulfovibrio, and Sulfuricurvum. The approach employed in the present study resolved the bacterial diversity present in these biofilm communities as well as the differences that occurred in biofilms within a single distribution system, and suggests that next-generation sequencing of 16S rRNA amplicons can show changes in bacterial biofilm communities associated with different water qualities.

The Water Safety Plan (WSP) methodology, which aims to enhance safety of drinking water supplies, has been recommended by the World Health Organization since 2004. WSPs are now used worldwide and are legally required in several countries. However, there is limited systematic evidence available demonstrating the effectiveness of WSPs on water quality and health. Iceland was one of the first countries to legislate the use of WSPs, enabling the analysis of more than a decade of data on impact of WSP. The objective was to determine the impact of WSP implementation on regulatory compliance, microbiological water quality, and incidence of clinical cases of diarrhea. Surveillance data on water quality and diarrhea were collected and analyzed. The results show that HPC (heterotrophic plate counts), representing microbiological growth in the water supply system, decreased statistically significant with fewer incidents of HPC exceeding 10 cfu per mL in samples following WSP implementation and noncompliance was also significantly reduced (p

Formulating effective management intervention measures for water supply systems requires investigation of potential long-term impacts. This study applies an integrated multiple regression, random forest regression, and quantitative microbial risk assessment (QMRA) modelling approach to assess the effect of climate-driven precipitation on pathogen infection risks in three drinking water treatment plants (WTPs) in Norway. Pathogen removal efficacies of treatment steps were calculated using process models. The results indicate that while the WTPs investigated generally meet the current water safety guidelines, risks of Norovirus and Cryptosporidium infection may be of concern in the future. The pathogen infections attributable to current projections of average precipitation in the study locations may be low. However, the pathogen increases in the drinking water sources due to the occurrence of extreme precipitation events in the catchments could substantially increase the risks of pathogen infections. In addition, without optimal operation of the UV disinfection steps in the WTPs, both the present and potential future infection risks could be high. Therefore, the QMRA models demonstrated the need for improved optimization of key treatment steps in the WTPs, as well as implementation of stringent regulations in protecting raw water sources in the country. The variety of models applied and the pathogen: E. coli used in the study introduce some uncertainties in the results, thus, management decisions that will be based on the results should consider these limitations. Nevertheless, the integration of predictive models with QMRA as applied in this study could be a useful method for climate impact assessment in the water supply industry.

Bacteria, protozoa and viruses are ubiquitous in aquatic environments and may pose threats to water quality for both human and ecosystem health. Microbial risk assessment and management in the water sector is a focus of governmental regulation and scientific inquiry; however, stark gaps remain in their application and interpretation. This paper evaluates how water managers practice microbial risk assessment and management in two Canadian provinces (BC and Ontario). We assess three types of entities engaged in water management along the source-to-tap spectrum (watershed agencies, water utilities, and public health authorities). We analyze and compare the approaches used by these agencies to assess and manage microbial risk (including scope, frequency, and tools). We evaluate key similarities and differences, and situate them with respect to international best practices derived from literatures related to microbial risk assessment and management. We find considerable variability in microbial risk assessment frameworks and management tools in that approaches 1) vary between provinces; 2) vary within provinces and between similar types of agencies; 3) have limited focus on microbial risk assessment for ecosystem health and 4) diverge considerably from the literature on best practices. We find that risk assessments that are formalized, routine and applied system-wide (i.e. from source-to-tap) are limited. We identify key limitations of current testing methodologies and looking forward consider the outcomes of this research within the context of new developments in microbial water quality monitoring such as tests derived from genomics and metagenomics based research.

Presently, concentrations of fecal indicator bacteria (FIB) in raw water sources are not known before water undergoes treatment, since analysis takes approximately 24h to produce results. Using data on water quality and environmental variables, models can be used to predict real time concentrations of FIB in raw water. This study evaluates the potentials of zero-inflated regression models (ZI), Random Forest regression model (RF) and adaptive neuro-fuzzy inference system (ANFIS) to predict the concentration of FIB in the raw water source of a water treatment plant in Norway. The ZI, RF and ANFIS faecal indicator bacteria predictive models were built using physico-chemical (pH, temperature, electrical conductivity, turbidity, color, and alkalinity) and catchment precipitation data from 2009 to 2015. The study revealed that pH, temperature, turbidity, and electrical conductivity in the raw water were the most significant factors associated with the concentration of FIB in the raw water source. Compared to the other models, the ANFIS model was superior (Mean Square Error=39.49, 0.35, 0.09, 0.23CFU/100ml respectively for coliform bacteria, E. coli, Intestinal enterococci and Clostridium perfringens) in predicting the variations of FIB in the raw water during model testing. However, the model was not capable of predicting low counts of FIB during both training and testing stages of the models. The ZI and RF models were more consistent when applied to testing data, and they predicted FIB concentrations that characterized the observed FIB concentrations. While these models might need further improvement, results of this study indicate that ZI and RF regression models have high prospects as tools for the real-time prediction of FIB in raw water sources for proactive microbial risk management in water treatment plants.

The wide circulation of Klebsiella bacteria in water ofwater objects of different climatic zones of Russia and various function is established. So bacteria of the Klebsiella strain are in superficial sources of the centralized water supply depending on extent of their biological and chemical pollution; underground waters at the unprotected water-bearing horizons; in drinking water at insufficiently effective system of its cleaning and disinfecting. Klebsiella circulating in water was shown to keep properties of pathogenicity and a virulence, possess resistance both to modern preparations and disinfecting agents (chlorine, an ultraviolet to radiation). Bacteria of the Klebsiella strain have high penetration in the water-bearing horizons. At strains of Klebsiella there is allocated considerable pathogenic potential (adhesive, invasive, phosphatase, lecithinase, DNA-ase, hemolytic activity) and genetic markers of pathogenicity of cnf-1. The etiologic role of bacteria of Klebsiella and an infecting (100, COE/dm3) dose emergence of acute intestinal infections (AII) is established. Detection of Klebsiella in water objects and especially in water of drinking appointment, in the absence of total coliform bacteria (TCB) contributes to the epidemic danger of water use.